Category Archives: Kudu

Up and running with Apache Spark on Apache Kudu

Categories: CDH Data Ingestion Data Science General Hadoop How-to Impala Kudu Spark Training Use Case

After the GA of Apache Kudu in Cloudera CDH 5.10, we take a look at the Apache Spark on Kudu integration, share code snippets, and explain how to get up and running quickly, as Kudu is already a first-class citizen in Spark’s ecosystem.

 

As the Apache Kudu development team celebrates the initial 1.0 release launched on September 19, and the most recent 1.2.0 version now GA as part of Cloudera’s CDH 5.10 release,

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Cloudera Enterprise 5.10 is Now Available

Categories: CDH Cloud Cloudera Manager Cloudera Navigator Hadoop Hue Kudu

Cloudera is proud to announce that Cloudera Enterprise 5.10 is now generally available (GA). The highlights of this release include the GA of the new columnar storage engine Apache Kudu, improved cloud performance and cost-optimizations, and cloud-native data governance for Amazon S3.

As usual, there are also a number of quality enhancements and bug fixes (learn more about our multi-dimensional hardening/QA process) and other improvements across the stack. Here is a partial list of what’s included (see the Release Notes for a full list):

  • GA of Apache Kudu

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Apache Kudu and Apache Impala (Incubating): The Integration Roadmap

Categories: Impala Kudu

Impala users can expect new performance and usability benefits via improved integration with Kudu.

It’s been nearly one year since the public beta announcement of Kudu (now a top-level Apache project) and a noteworthy milestone has been reached: its 1.0 release. This is particularly exciting as Kudu extends the use cases that can be supported on the Apache Hadoop platform, whether it be on-premises or in the cloud,

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New in Cloudera Labs: Envelope (for Apache Spark Streaming)

Categories: Cloudera Labs Data Ingestion Kafka Kudu

As a warm-up to Spark Summit West in San Francisco (June 6-8),  we’ve added a new project to Cloudera Labs that makes building Spark Streaming pipelines considerably easier.

Spark Streaming is the go-to engine for stream processing in the Cloudera stack. It allows developers to build stream data pipelines that harness the rich Spark API for parallel processing, expressive transformations, fault tolerance, and exactly-once processing. But it requires a programmer to write code,

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How-to: Build a Prediction Engine using Spark, Kudu, and Impala

Categories: Guest Impala Kudu Spark

Thanks to Richard Williamson of Silicon Valley Data Science for allowing us to republish the following post about his sample application based on Apache Spark, Apache Kudu (incubating), and Apache Impala (incubating).

Why should your infrastructure maintain a linear growth pattern when your business scales up and down during the day based on natural human cycles? There is an obvious need to maintain a steady baseline infrastructure to keep the lights on for your business,

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